Keywords
urban dynamics; historical vector topographic database; time series; clustering; dynamic time warping; edit-distance.
Location
Session C1: VI Data Mining for Environmental Sciences Session
Start Date
13-7-2016 11:30 AM
End Date
13-7-2016 11:50 AM
Abstract
This article introduces a new methodology dedicated to extracting the evolution of urban blocks from spatiotemporal topographic databases where an urban block is defined as the smallest area that is surrounded by communication network. To achieve this analysis, we apply the ascendant hierarchical clustering to sequences of urban block states (i.e.; sequences of class labels to which the block belongs to on each date). The principal originality of this approach is to use a measure based on DTW (Dynamic Time Warping) which is able to apprehend temporal behaviours (mainly time lags in dates corresponding to a change of state) and which takes into account the semantic proximity between the different kinds of urban blocks. Several experiments have been carried out on areas in the city of Strasbourg (France). First results are relevant and highlight realistic urban dynamics.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Spatial Evolution of Urban Fabrics Extracted from Spatiotemporal Topographic Database using Symbolic Dynamic Time Warping
Session C1: VI Data Mining for Environmental Sciences Session
This article introduces a new methodology dedicated to extracting the evolution of urban blocks from spatiotemporal topographic databases where an urban block is defined as the smallest area that is surrounded by communication network. To achieve this analysis, we apply the ascendant hierarchical clustering to sequences of urban block states (i.e.; sequences of class labels to which the block belongs to on each date). The principal originality of this approach is to use a measure based on DTW (Dynamic Time Warping) which is able to apprehend temporal behaviours (mainly time lags in dates corresponding to a change of state) and which takes into account the semantic proximity between the different kinds of urban blocks. Several experiments have been carried out on areas in the city of Strasbourg (France). First results are relevant and highlight realistic urban dynamics.
